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https://github.com/triqs/dft_tools
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63 lines
2.4 KiB
ReStructuredText
63 lines
2.4 KiB
ReStructuredText
.. _Design:
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Strategy
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=============================================================
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All the classes are a combination of a system of indices (called IndexMap I in the following)
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and a physical storage S in the computer (a block of memory), denoted as an IndexMap_Storage_Pair (I,S).
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* I models the IndexMap concept [REF below].
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* It is the bijection between the a set of indices and the position in the memory block. It can be though as a coordinate system on the (linear) memory block.
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* Various types of indices are possible (only the first is implemented now).
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* cuboid (the standard hypercubic array, the only one currently implemented)
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* triangular arrays
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* band matrix
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* multi-indices, with indices made of pair<int,int> e.g.
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* S models the Storage concept [REF].
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* It is a handle to the memory block containing the actual data.
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* It can be e.g.:
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* a C++ shared pointer to a memory block.
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* a reference to a numpy array.
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This design has several consequences :
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* **Interoperability** : classes are widely interoperable, e.g. one can add a array and a matrix (if dimensions are ok of course).
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one can also add a python numpy and a C++ array without any further coding.
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* It is straighforward to construct a matrix_view<T> from an array<T,2>, since it is the same couple <I,S>,
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just interpreted differently.
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* It is easy to view a array<T,4> as a matrix by gathering indices (properly ordered in memory) :
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one just has to provide a new IndexMap I2 to see the same data.
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[ --> very useful for vertex computation in many body...]
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* Slicing, or partial view is very natural : it is just a function on indexmaps : I--> I2,
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independantly of any storage.
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Quick guide through the implementation
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=============================================================
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The implementation is divided into basically 4 parts :
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* Storages : implements two storages shared_block and numpy
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* IndexMaps : implements cuboid index map, its domain and iterators
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* impl/indexmap_storage_pair.hpp : the basic implementation class for all user class.
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It is basically just a couple of an indexmap and a storage, with shallow copy.
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It also forward the slices to the indexmap and construct the correct views.
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* upper level :
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* user class : array, array_view, matrix, matrix_view, vector, vector_view
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* expression.hpp : boost proto expression
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* numpy_interface.hpp : helper to get numpy into array
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* lapack/blas interface
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* hdf5 support.
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